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Build sophisticated multi-agent AI systems where specialized agents collaborate to complete complex business tasks using StackOne’s unified API access.

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Overview

  • Multi-agent collaboration with business data access
  • Specialized agents for different business functions
  • Complex workflow automation with task dependencies
  • Enhanced error handling and monitoring
from crewai import Agent, Crew, Task
from stackone_ai import StackOneToolSet

# Initialize tools and create agents
toolset = StackOneToolSet()
tools = toolset.get_tools("hris_*", account_id="your-account-id")
langchain_tools = tools.to_langchain()

# Create specialized agents
hr_manager = Agent(
    role="HR Manager",
    goal="Manage employee data and handle HR requests",
    backstory="Expert in human resources with experience in employee management",
    tools=langchain_tools,
    verbose=True
)

recruiter = Agent(
    role="Recruiter",
    goal="Find and evaluate candidates for open positions",
    backstory="Experienced recruiter with talent acquisition expertise",
    tools=toolset.get_tools("ats_*", account_id="your-account-id").to_langchain(),
    verbose=True
)

# Create collaborative tasks
employee_analysis_task = Task(
    description="Analyze current employee distribution by department",
    agent=hr_manager,
    expected_output="Employee distribution report with staffing recommendations"
)

# Execute multi-agent crew
crew = Crew(
    agents=[hr_manager, recruiter],
    tasks=[employee_analysis_task],
    verbose=True
)

result = crew.kickoff()
print(result)

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Complete Examples

GitHub Examples: For detailed implementations including multi-agent hiring workflows, onboarding automation, and performance monitoring:→ View CrewAI Integration ExamplesFor CrewAI multi-agent patterns and framework guides, see the CrewAI documentation.